[CI] Update circle-ci and github workflow. (#1018)

* Add deploy workflow.

* [CI] Update circle-ci and github workflow.

* Fix windows CI

* Update unit tests to save memory

.circleci/test.yml

@@ -31,7 +31,7 @@ jobs:
           name: Check docstring coverage
           command: |
             pip install interrogate
-            interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-regex "__repr__" --fail-under 60 mmcls
+            interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-magic --ignore-regex "__repr__" --fail-under 60 mmcls
   build_cpu:
     parameters:
       # The python version must match available image tags in
@@ -42,8 +42,6 @@ jobs:
         type: string
       torchvision:
         type: string
-      mmcv:
-        type: string
     docker:
       - image: cimg/python:<< parameters.python >>
     resource_class: large
@@ -57,31 +55,32 @@ jobs:
       - run:
           name: Configure Python & pip
           command: |
-            python -m pip install --upgrade pip
-            python -m pip install wheel
+            pip install --upgrade pip
+            pip install wheel
       - run:
           name: Install PyTorch
           command: |
             python -V
-            python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
+            pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
       - run:
           name: Install mmcls dependencies
           command: |
-            python -m pip install git+ssh://git@github.com/open-mmlab/mmengine.git@main
-            python -m pip install << parameters.mmcv >>
-            python -m pip install timm
-            python -m pip install -r requirements.txt
+            pip install git+https://github.com/open-mmlab/mmengine.git@main
+            pip install -U openmim
+            mim install 'mmcv >= 2.0.0rc1'
+            pip install timm
+            pip install -r requirements.txt
             python -c 'import mmcv; print(mmcv.__version__)'
       - run:
           name: Build and install
           command: |
-            python -m pip install -e .
+            pip install -e .
       - run:
           name: Run unittests
           command: |
-            python -m coverage run --branch --source mmcls -m pytest tests/
-            python -m coverage xml
-            python -m coverage report -m
+            coverage run --branch --source mmcls -m pytest tests/
+            coverage xml
+            coverage report -m
 
   build_cuda:
     machine:
@@ -96,15 +95,13 @@ jobs:
       cudnn:
         type: integer
         default: 7
-      mmcv:
-        type: string
     steps:
       - checkout
       - run:
           # Cloning repos in VM since Docker doesn't have access to the private key
           name: Clone Repos
           command: |
-            git clone -b main --depth 1 ssh://git@github.com/open-mmlab/mmengine.git /home/circleci/mmengine
+            git clone -b main --depth 1 https://github.com/open-mmlab/mmengine.git /home/circleci/mmengine
       - run:
           name: Build Docker image
           command: |
@@ -114,7 +111,8 @@ jobs:
           name: Install mmcls dependencies
           command: |
             docker exec mmcls pip install -e /mmengine
-            docker exec mmcls pip install << parameters.mmcv >>
+            docker exec mmcls pip install -U openmim
+            docker exec mmcls mim install 'mmcv >= 2.0.0rc1'
             docker exec mmcls pip install -r requirements.txt
             docker exec mmcls python -c 'import mmcv; print(mmcv.__version__)'
       - run:
@@ -124,7 +122,7 @@ jobs:
       - run:
           name: Run unittests
           command: |
-            docker exec mmcls python -m pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
+            docker exec mmcls python -m pytest tests/ -k 'not timm'
 
 # Invoke jobs via workflows
 # See: https://circleci.com/docs/2.0/configuration-reference/#workflows
@@ -138,6 +136,7 @@ workflows:
             branches:
               ignore:
                 - dev-1.x
+                - 1.x
   pr_stage_test:
     when:
       not:
@@ -154,15 +153,13 @@ workflows:
           torch: 1.6.0
           torchvision: 0.7.0
           python: 3.6.9  # The lowest python 3.6.x version available on CircleCI images
-          mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cpu/torch1.6.0/mmcv_full-2.0.0rc0-cp36-cp36m-manylinux1_x86_64.whl
           requires:
             - lint
       - build_cpu:
           name: maximum_version_cpu
-          torch: 1.9.0  # TODO: Update the version after mmcv provides more pre-compiled packages.
-          torchvision: 0.10.0
+          torch: 1.12.1
+          torchvision: 0.13.1
           python: 3.9.0
-          mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cpu/torch1.9.0/mmcv_full-2.0.0rc0-cp39-cp39-manylinux1_x86_64.whl
           requires:
             - minimum_version_cpu
       - hold:
@@ -175,7 +172,6 @@ workflows:
           # Use double quotation mark to explicitly specify its type
           # as string instead of number
           cuda: "10.2"
-          mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cu102/torch1.8.0/mmcv_full-2.0.0rc0-cp37-cp37m-manylinux1_x86_64.whl
           requires:
             - hold
   merge_stage_test:
@@ -188,7 +184,6 @@ workflows:
           torch: 1.6.0
           # Use double quotation mark to explicitly specify its type
           # as string instead of number
-          mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cu101/torch1.6.0/mmcv_full-2.0.0rc0-cp37-cp37m-manylinux1_x86_64.whl
           cuda: "10.1"
           filters:
             branches:

.github/workflows/lint.yml

@@ -0,0 +1,27 @@
+name: lint
+
+on: [push, pull_request]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.7
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+      - name: Install pre-commit hook
+        run: |
+          pip install pre-commit
+          pre-commit install
+      - name: Linting
+        run: pre-commit run --all-files
+      - name: Check docstring coverage
+        run: |
+          pip install interrogate
+          interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-magic --ignore-regex "__repr__" --fail-under 60 mmcls

.github/workflows/pr_stage_test.yml

@@ -0,0 +1,87 @@
+name: pr_stage_test
+
+on:
+  pull_request:
+    paths-ignore:
+      - 'README.md'
+      - 'README_zh-CN.md'
+      - 'docs/**'
+      - 'demo/**'
+      - 'tools/**'
+      - 'configs/**'
+      - '.dev_scripts/**'
+      - '.circleci/**'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build:
+    runs-on: ubuntu-18.04
+    strategy:
+      matrix:
+        python-version: [3.7]
+        include:
+          - torch: 1.8.1
+            torchvision: 0.9.1
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Upgrade pip
+        run: pip install pip --upgrade
+      - name: Install PyTorch
+        run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Install mmcls dependencies
+        run: |
+          pip install git+https://github.com/open-mmlab/mmengine.git@main
+          pip install -U openmim
+          mim install 'mmcv >= 2.0.0rc1'
+          pip install -r requirements.txt
+      - name: Build and install
+        run: pip install -e .
+      - name: Run unittests and generate coverage report
+        run: |
+          coverage run --branch --source mmcls -m pytest tests/ -k 'not timm'
+          coverage xml
+          coverage report -m
+      # Upload coverage report for python3.7 && pytorch1.8.1 cpu
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v1.0.14
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella
+          fail_ci_if_error: false
+
+  build_windows:
+    runs-on: windows-2022
+    strategy:
+      matrix:
+        python: [3.7]
+        platform: [cu111]
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Upgrade pip
+        run: pip install pip --upgrade
+      - name: Install PyTorch
+        run: pip install torch==1.8.2+${{matrix.platform}} torchvision==0.9.2+${{matrix.platform}} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
+      - name: Install mmcls dependencies
+        run: |
+          pip install git+https://github.com/open-mmlab/mmengine.git@main
+          pip install -U openmim
+          mim install 'mmcv >= 2.0.0rc1'
+          pip install -r requirements.txt
+      - name: Build and install
+        run: pip install -e .
+      - name: Run unittests
+        run: |
+          pytest tests/ -k 'not timm' --ignore tests/test_models/test_backbones

.github/workflows/publish-to-pypi.yml

@@ -0,0 +1,22 @@
+name: deploy
+
+on: push
+
+jobs:
+  build-n-publish:
+    runs-on: ubuntu-latest
+    if: startsWith(github.event.ref, 'refs/tags')
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.7
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+      - name: Build MMClassification
+        run: |
+          pip install wheel
+          python setup.py sdist bdist_wheel
+      - name: Publish distribution to PyPI
+        run: |
+          pip install twine
+          twine upload dist/* -u __token__ -p ${{ secrets.pypi_password }}

.github/workflows/test_mim.yml

@@ -0,0 +1,44 @@
+name: test-mim
+
+on:
+  push:
+    paths:
+      - 'model-index.yml'
+      - 'configs/**'
+
+  pull_request:
+    paths:
+      - 'model-index.yml'
+      - 'configs/**'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build_cpu:
+    runs-on: ubuntu-18.04
+    strategy:
+      matrix:
+        python-version: [3.7]
+        torch: [1.8.0]
+        include:
+          - torch: 1.8.0
+            torch_version: torch1.8
+            torchvision: 0.9.0
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Upgrade pip
+        run: pip install pip --upgrade
+      - name: Install PyTorch
+        run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Install openmim
+        run: pip install openmim
+      - name: Build and install
+        run: mim install -e .
+      - name: test commands of mim
+        run: mim search mmcls

mmcls/datasets/transforms/processing.py

@@ -504,7 +504,8 @@ class RandomErasing(BaseTransform):
             'aspect_range should be positive.'
         assert aspect_range[0] <= aspect_range[1], \
             'In aspect_range (min, max), min should be smaller than max.'
-        assert mode in ['const', 'rand']
+        assert mode in ['const', 'rand'], \
+            'Please select `mode` from ["const", "rand"].'
         if isinstance(fill_color, Number):
             fill_color = [fill_color] * 3
         assert isinstance(fill_color, Sequence) and len(fill_color) == 3 \

tests/test_datasets/test_datasets.py

@@ -2,6 +2,7 @@
 import os
 import os.path as osp
 import pickle
+import sys
 import tempfile
 from unittest import TestCase
 from unittest.mock import MagicMock, call, patch
@@ -141,12 +142,12 @@ class TestCustomDataset(TestBaseDataset):
         self.assertEqual(dataset.CLASSES, ('a', 'b'))  # auto infer classes
         self.assertGreaterEqual(
             dataset.get_data_info(0).items(), {
-                'img_path': osp.join(ASSETS_ROOT, 'a/1.JPG'),
+                'img_path': osp.join(ASSETS_ROOT, 'a', '1.JPG'),
                 'gt_label': 0
             }.items())
         self.assertGreaterEqual(
             dataset.get_data_info(2).items(), {
-                'img_path': osp.join(ASSETS_ROOT, 'b/subb/3.jpg'),
+                'img_path': osp.join(ASSETS_ROOT, 'b', 'subb', '3.jpg'),
                 'gt_label': 1
             }.items())
 
@@ -225,7 +226,7 @@ class TestCustomDataset(TestBaseDataset):
         self.assertEqual(len(dataset), 1)
         self.assertGreaterEqual(
             dataset.get_data_info(0).items(), {
-                'img_path': osp.join(ASSETS_ROOT, 'b/2.jpeg'),
+                'img_path': osp.join(ASSETS_ROOT, 'b', '2.jpeg'),
                 'gt_label': 1
             }.items())
 
@@ -631,12 +632,12 @@ class TestVOC(TestBaseDataset):
         # Test different backend
         cfg = {
             **self.DEFAULT_ARGS, 'lazy_init': True,
-            'data_root': 's3:/openmmlab/voc'
+            'data_root': 's3://openmmlab/voc'
         }
+        petrel_mock = MagicMock()
+        sys.modules['petrel_client'] = petrel_mock
         dataset = dataset_class(**cfg)
-        dataset._check_integrity = MagicMock(return_value=False)
-        with self.assertRaisesRegex(FileNotFoundError, 's3:/openmmlab/voc'):
-            dataset.full_init()
+        petrel_mock.client.Client.assert_called()
 
     def test_extra_repr(self):
         dataset_class = DATASETS.get(self.DATASET_TYPE)

tests/test_engine/test_hooks/test_precise_bn_hook.py

@@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
-import shutil
+import logging
 import tempfile
 from unittest import TestCase
 from unittest.mock import MagicMock, patch
@@ -8,6 +8,7 @@ from unittest.mock import MagicMock, patch
 import pytest
 import torch
 import torch.nn as nn
+from mmengine.logging import MMLogger
 from mmengine.model import BaseDataPreprocessor, BaseModel
 from mmengine.runner import Runner
 from torch.utils.data import DataLoader, Dataset
@@ -115,7 +116,7 @@ class TestPreciseBNHookHook(TestCase):
         )
         self.epoch_train_cfg = dict(by_epoch=True, max_epochs=1)
         self.iter_train_cfg = dict(by_epoch=False, max_iters=5)
-        self.tmpdir = tempfile.mkdtemp()
+        self.tmpdir = tempfile.TemporaryDirectory()
         self.preciseBN_cfg = copy.deepcopy(self.DEFAULT_ARGS)
 
         test_dataset = ExampleDataset()
@@ -125,7 +126,7 @@ class TestPreciseBNHookHook(TestCase):
     def test_construct(self):
         self.runner = Runner(
             model=self.model,
-            work_dir=self.tmpdir,
+            work_dir=self.tmpdir.name,
             train_dataloader=self.loader,
             train_cfg=self.epoch_train_cfg,
             log_level='WARNING',
@@ -160,7 +161,7 @@ class TestPreciseBNHookHook(TestCase):
         self.preciseBN_cfg['priority'] = 'ABOVE_NORMAL'
         self.runner = Runner(
             model=self.model,
-            work_dir=self.tmpdir,
+            work_dir=self.tmpdir.name,
             train_dataloader=self.loader,
             train_cfg=self.epoch_train_cfg,
             log_level='WARNING',
@@ -176,7 +177,7 @@ class TestPreciseBNHookHook(TestCase):
         self.preciseBN_cfg['priority'] = 'ABOVE_NORMAL'
         self.runner = Runner(
             model=self.model,
-            work_dir=self.tmpdir,
+            work_dir=self.tmpdir.name,
             train_dataloader=self.loader,
             train_cfg=self.epoch_train_cfg,
             log_level='WARNING',
@@ -213,7 +214,7 @@ class TestPreciseBNHookHook(TestCase):
         self.loader = DataLoader(test_dataset, batch_size=2)
         self.runner = Runner(
             model=self.model,
-            work_dir=self.tmpdir,
+            work_dir=self.tmpdir.name,
             train_dataloader=self.loader,
             train_cfg=self.iter_train_cfg,
             log_level='WARNING',
@@ -226,4 +227,8 @@ class TestPreciseBNHookHook(TestCase):
         self.runner.train()
 
     def tearDown(self) -> None:
-        shutil.rmtree(self.tmpdir)
+        # `FileHandler` should be closed in Windows, otherwise we cannot
+        # delete the temporary directory.
+        logging.shutdown()
+        MMLogger._instance_dict.clear()
+        self.tmpdir.cleanup()

tests/test_models/test_backbones/test_conformer.py

@@ -25,6 +25,7 @@ def check_norm_state(modules, train_state):
     return True
 
 
+@torch.no_grad()  # To save memory
 def test_conformer_backbone():
 
     cfg_ori = dict(

tests/test_models/test_backbones/test_convmixer.py

@@ -18,6 +18,7 @@ def test_assertion():
         ConvMixer(out_indices=-100)
 
 
+@torch.no_grad()  # To save memory
 def test_convmixer():
 
     # Test forward